MIROC5 model output prepared for CMIP5 RCP8.5
Load in Python
from intake import open_catalog
cat = open_catalog("https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cl_Amon_MIROC5_rcp85_r1i1p1.yaml")
ds=cat.netcdf.read()Metadata
| title | MIROC5 model output prepared for CMIP5 RCP8.5 |
| location | /shared/cmip5/data/rcp85/atmos/mon/Amon/cl/MIROC.MIROC5/r1i1p1 |
| tags | gridded,global,model,monthly |
| catalog_dir | https://raw.githubusercontent.com/kpegion/COLA-DATASETS-CATALOG/gh-pages/intake-catalogs/cl_Amon_MIROC5_rcp85_r1i1p1.yaml |
| last updated | 2013-06-14 |
Dataset Contents
<xarray.Dataset>
Dimensions: (bnds: 2, lat: 128, lev: 40, lon: 256, time: 1140)
Coordinates:
* time (time) float64 5.696e+04 5.698e+04 ... 9.157e+04 9.16e+04
* lev (lev) float64 0.9975 0.9915 0.983 ... 0.01861 0.0106 0.002905
* lat (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93
* lon (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6
Dimensions without coordinates: bnds
Data variables:
time_bnds (time, bnds) float64 dask.array<chunksize=(48, 2), meta=np.ndarray>
lev_bnds (time, lev, bnds) float64 dask.array<chunksize=(48, 40, 2), meta=np.ndarray>
p0 (time) float32 100000.0 100000.0 100000.0 ... 100000.0 100000.0
a (time, lev) float64 dask.array<chunksize=(48, 40), meta=np.ndarray>
b (time, lev) float64 dask.array<chunksize=(48, 40), meta=np.ndarray>
ps (time, lat, lon) float32 dask.array<chunksize=(48, 128, 256), meta=np.ndarray>
a_bnds (time, lev, bnds) float64 dask.array<chunksize=(48, 40, 2), meta=np.ndarray>
b_bnds (time, lev, bnds) float64 dask.array<chunksize=(48, 40, 2), meta=np.ndarray>
lat_bnds (time, lat, bnds) float64 dask.array<chunksize=(48, 128, 2), meta=np.ndarray>
lon_bnds (time, lon, bnds) float64 dask.array<chunksize=(48, 256, 2), meta=np.ndarray>
cl (time, lev, lat, lon) float32 dask.array<chunksize=(48, 40, 128, 256), meta=np.ndarray>
Attributes:
institution: AORI (Atmosphere and Ocean Research Institute, Th...
institute_id: MIROC
experiment_id: rcp85
source: MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...
model_id: MIROC5
forcing: GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...
parent_experiment_id: historical
parent_experiment_rip: r1i1p1
branch_time: 56940.0
contact: Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seit...
references: Watanabe et al., 2010: Improved climate simulatio...
initialization_method: 1
physics_version: 1
tracking_id: e8e8aab9-e113-4a8b-8fb6-0220ced9c460
product: output
experiment: RCP8.5
frequency: mon
creation_date: 2011-09-02T08:35:10Z
history: 2011-09-02T08:35:10Z CMOR rewrote data to comply ...
Conventions: CF-1.4
project_id: CMIP5
table_id: Table Amon (27 April 2011) a5a1c518f52ae340313ba0...
title: MIROC5 model output prepared for CMIP5 RCP8.5
parent_experiment: historical
modeling_realm: atmos
realization: 1
cmor_version: 2.7.1xarray.Dataset
- bnds: 2
- lat: 128
- lev: 40
- lon: 256
- time: 1140
- time(time)float645.696e+04 5.698e+04 ... 9.16e+04
- bounds :
- time_bnds
- units :
- days since 1850-1-1
- calendar :
- noleap
- axis :
- T
- long_name :
- time
- standard_name :
- time
array([56955.5, 56985. , 57014.5, ..., 91538.5, 91569. , 91599.5])
- lev(lev)float640.9975 0.9915 ... 0.0106 0.002905
- bounds :
- lev_bnds
- units :
- 1
- axis :
- Z
- positive :
- down
- long_name :
- hybrid sigma pressure coordinate
- standard_name :
- atmosphere_hybrid_sigma_pressure_coordinate
- formula :
- p = a*p0 + b*ps
- formula_terms :
- p0: p0 a: a b: b ps: ps
array([0.997499, 0.991499, 0.982997, 0.971996, 0.958493, 0.94199 , 0.922486, 0.900483, 0.875977, 0.848972, 0.819967, 0.786951, 0.746923, 0.698885, 0.642833, 0.574472, 0.501478, 0.43645 , 0.379852, 0.330596, 0.287725, 0.250411, 0.21794 , 0.189681, 0.16508 , 0.143673, 0.125043, 0.108828, 0.094716, 0.082434, 0.071745, 0.062441, 0.054278, 0.046937, 0.040158, 0.033613, 0.026593, 0.018613, 0.010603, 0.002905]) - lat(lat)float64-88.93 -87.54 ... 87.54 88.93
- bounds :
- lat_bnds
- units :
- degrees_north
- axis :
- Y
- long_name :
- latitude
- standard_name :
- latitude
array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466, -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389, -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251, -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857, -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361, -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816, -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244, -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655, -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057, -13.30729 , -11.906523, -10.505756, -9.104989, -7.704221, -6.303454, -4.902687, -3.501919, -2.101151, -0.700384, 0.700384, 2.101151, 3.501919, 4.902687, 6.303454, 7.704221, 9.104989, 10.505756, 11.906523, 13.30729 , 14.708057, 16.108824, 17.509591, 18.910357, 20.311124, 21.71189 , 23.112655, 24.513421, 25.914186, 27.314951, 28.715716, 30.11648 , 31.517244, 32.918007, 34.31877 , 35.719532, 37.120294, 38.521056, 39.921816, 41.322576, 42.723335, 44.124093, 45.52485 , 46.925606, 48.326361, 49.727115, 51.127867, 52.528617, 53.929366, 55.330112, 56.730857, 58.131598, 59.532337, 60.933072, 62.333803, 63.73453 , 65.135251, 66.535966, 67.936673, 69.337372, 70.738059, 72.138732, 73.539389, 74.940023, 76.340629, 77.741196, 79.14171 , 80.542146, 81.942466, 83.342596, 84.742386, 86.141472, 87.538705, 88.927735]) - lon(lon)float640.0 1.406 2.812 ... 357.2 358.6
- bounds :
- lon_bnds
- units :
- degrees_east
- axis :
- X
- long_name :
- longitude
- standard_name :
- longitude
array([ 0. , 1.40625, 2.8125 , ..., 355.78125, 357.1875 , 358.59375])
- time_bnds(time, bnds)float64dask.array<chunksize=(48, 2), meta=np.ndarray>
Array Chunk Bytes 18.24 kB 1.92 kB Shape (1140, 2) (120, 2) Count 33 Tasks 11 Chunks Type float64 numpy.ndarray - lev_bnds(time, lev, bnds)float64dask.array<chunksize=(48, 40, 2), meta=np.ndarray>
- formula :
- p = a*p0 + b*ps
- standard_name :
- atmosphere_hybrid_sigma_pressure_coordinate
- units :
- 1
- formula_terms :
- p0: p0 a: a_bnds b: b_bnds ps: ps
Array Chunk Bytes 729.60 kB 76.80 kB Shape (1140, 40, 2) (120, 40, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - p0(time)float32100000.0 100000.0 ... 100000.0
- long_name :
- vertical coordinate formula term: reference pressure
- units :
- Pa
array([100000., 100000., 100000., ..., 100000., 100000., 100000.], dtype=float32) - a(time, lev)float64dask.array<chunksize=(48, 40), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: a(k)
Array Chunk Bytes 364.80 kB 38.40 kB Shape (1140, 40) (120, 40) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - b(time, lev)float64dask.array<chunksize=(48, 40), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k)
Array Chunk Bytes 364.80 kB 38.40 kB Shape (1140, 40) (120, 40) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - ps(time, lat, lon)float32dask.array<chunksize=(48, 128, 256), meta=np.ndarray>
- standard_name :
- surface_air_pressure
- long_name :
- Surface Air Pressure
- comment :
- not, in general, the same as mean sea-level pressure
- units :
- Pa
- original_units :
- hPa
- history :
- 2011-09-02T08:35:10Z altered by CMOR: Converted units from 'hPa' to 'Pa'.
- cell_methods :
- time: mean
- cell_measures :
- area: areacella
Array Chunk Bytes 149.42 MB 15.73 MB Shape (1140, 128, 256) (120, 128, 256) Count 33 Tasks 11 Chunks Type float32 numpy.ndarray - a_bnds(time, lev, bnds)float64dask.array<chunksize=(48, 40, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: a(k+1/2)
Array Chunk Bytes 729.60 kB 76.80 kB Shape (1140, 40, 2) (120, 40, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - b_bnds(time, lev, bnds)float64dask.array<chunksize=(48, 40, 2), meta=np.ndarray>
- long_name :
- vertical coordinate formula term: b(k+1/2)
Array Chunk Bytes 729.60 kB 76.80 kB Shape (1140, 40, 2) (120, 40, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - lat_bnds(time, lat, bnds)float64dask.array<chunksize=(48, 128, 2), meta=np.ndarray>
Array Chunk Bytes 2.33 MB 245.76 kB Shape (1140, 128, 2) (120, 128, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - lon_bnds(time, lon, bnds)float64dask.array<chunksize=(48, 256, 2), meta=np.ndarray>
Array Chunk Bytes 4.67 MB 491.52 kB Shape (1140, 256, 2) (120, 256, 2) Count 44 Tasks 11 Chunks Type float64 numpy.ndarray - cl(time, lev, lat, lon)float32dask.array<chunksize=(48, 40, 128, 256), meta=np.ndarray>
- standard_name :
- cloud_area_fraction_in_atmosphere_layer
- long_name :
- Cloud Area Fraction
- comment :
- Includes both large-scale and convective cloud.
- units :
- %
- original_name :
- CLDFRC
- history :
- 2011-09-02T08:35:10Z altered by CMOR: Converted units from '' to '%'. 2011-09-02T08:35:10Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-09-02T08:35:10Z altered by CMOR: Inverted axis: lat.
- cell_methods :
- time: mean
- cell_measures :
- area: areacella
- associated_files :
- baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_rcp85_r0i0p0.nc areacella: areacella_fx_MIROC5_rcp85_r0i0p0.nc
Array Chunk Bytes 5.98 GB 629.15 MB Shape (1140, 40, 128, 256) (120, 40, 128, 256) Count 33 Tasks 11 Chunks Type float32 numpy.ndarray
- institution :
- AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)
- institute_id :
- MIROC
- experiment_id :
- rcp85
- source :
- MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)
- model_id :
- MIROC5
- forcing :
- GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)
- parent_experiment_id :
- historical
- parent_experiment_rip :
- r1i1p1
- branch_time :
- 56940.0
- contact :
- Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)
- references :
- Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335
- initialization_method :
- 1
- physics_version :
- 1
- tracking_id :
- e8e8aab9-e113-4a8b-8fb6-0220ced9c460
- product :
- output
- experiment :
- RCP8.5
- frequency :
- mon
- creation_date :
- 2011-09-02T08:35:10Z
- history :
- 2011-09-02T08:35:10Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.
- Conventions :
- CF-1.4
- project_id :
- CMIP5
- table_id :
- Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862
- title :
- MIROC5 model output prepared for CMIP5 RCP8.5
- parent_experiment :
- historical
- modeling_realm :
- atmos
- realization :
- 1
- cmor_version :
- 2.7.1